Organ-on-a-chip technology has recently presented new tools for studying cellular and micro-organ function within a 3D environment mimicking native organ structures. However, in these enclosed systems, it remains difficult to evaluate the health and function of live cells contained within these devices without retroactive fixation and antibody staining. Secreted protein biomarkers may provide an opportunity to non- invasively evaluate the health and function of these cells, although the tools to reliably sense these biomarkers in real-time have yet to be developed. We have recently applied an organ-on-a-chip approach to study the metabolic disorder diabetes. In healthy individuals, pancreatic islet structures secrete the small molecule insulin to negatively regulate blood glucose levels, a process that is disrupted in diabetic individuals resulting in elevated blood glucose levels. In order to study the mechanisms underlying defective islet function ex vivo, we have recently incorporated human pancreatic islets within a 3D, vascularized organ-on-a-chip platform which mimics the pancreas in vivo. To fully exploit this platform, a simple, reliable, and real-time method for sensing the secreted biomarker insulin is necessary to evaluate islet function within the chip. Here, we propose to design, develop, and validate a receptor-based, bioluminescent imaging approach to optimize the real-time detection of small protein biomarkers. Specifically, we will utilize split luciferase constructs coupled to the human insulin receptor and its substrate, IRS-1, to detect insulin binding, using light output as a read-out of insulin concentration. The sensitivity and specificity of these tools will be extensively validated in two developmental phases: static 2D culture; followed by application in a 3D, biomimetic pancreas-on-a-chip platform. While this proposal focuses on developing these tools for insulin detection, our approach has broad implications in the detection of other secreted biomarkers in both static culture and dynamic microfluidic platforms.